Neural Machine Translation
Deep learning is revolutionizing how machine translation systems are built today. This introduction to machine translation starts from the basics of neural network methods and reaches the state of the art, while giving illuminating historical, linguistic, and applied context. Code examples in Python give a hands-on blueprint for implementation.
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V210:
Noch nicht erschienen, Januar 2021
Produktdetails
- ISBN: 978-1-108-49732-9
- EAN: 9781108497329
- Produktnummer: 33353166
- Verlag: Cambridge Academic
- Sprache: Englisch
- Erscheinungsjahr: 2020
- Seitenangabe: 200 S.
Über den Autor
Philipp Koehn is a leading researcher in the field of machine translation and Professor of Computer Science at Johns Hopkins University. In 2010 he authored the textbook Statistical Machine Translation (Cambridge). He received the Award of Honor from the International Association for Machine Translation and was one of three finalists for the European Inventor Award of the European Patent Office in 2013. Professor Koehn also works actively in industry as Chief Scientist for Omniscien Technology and as a consultant for Facebook.
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